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Approximate Throughput Computation of Stochastic Marked Graphs
July 1994 (vol. 20 no. 7)
pp. 526-535

A general iterative technique for approximate throughput computation of stochastic strongly connected marked graphs is presented. It generalizes a previous technique based on net decomposition through a single input-single output cut, allowing the split of the model through any cut. The approach has two basic foundations. First, a deep understanding of the qualitative behavior of marked graphs leads to a general decomposition technique. Second, after the decomposition phase, an iterative response time approximation method is applied for the computation of the throughput. Experimental results on several examples generally have an error of less than 3%. The state space is usually reduced by more than one order of magnitude; therefore, the analysis of otherwise intractable systems is possible.

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Index Terms:
Petri nets; stochastic processes; performance evaluation; approximate throughput computation; stochastic marked graphs; iterative technique; stochastic strongly connected marked graphs; net decomposition; single input-single output cut; qualitative behavior; general decomposition technique; iterative response time approximation method; error; state space; intractable systems; stochastic Petri net models
Citation:
J. Campos, J.M. Colom, H. Jungnitz, M. Silva, "Approximate Throughput Computation of Stochastic Marked Graphs," IEEE Transactions on Software Engineering, vol. 20, no. 7, pp. 526-535, July 1994, doi:10.1109/32.297941
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